Syncopy can be installed using conda:
We recommend to install SynCoPy into a new conda environment:
conda create -y --name syncopy esi-syncopy
conda activate syncopy
If you’re working on the ESI cluster installing Syncopy is only necessary if you create your own Conda environment.
Installing parallel processing engine ACME#
To harness the parallel processing capabilities of Syncopy on the ESI cluster it is helpful to install ACME.
Again either via conda
conda install -c conda-forge esi-acme
pip install esi-acme
See Parallel Processing for details about parallel processing setup
To start using Syncopy you have to import it in your Python code:
import syncopy as spy
All user-facing functions and classes can then be
accessed with the
spy. prefix, e.g.
To display your Syncopy version, run:
Setting Up Your Python Environment#
On the ESI cluster,
/opt/conda/envs/syncopy provides a
pre-configured and tested Conda environment with the most recent Syncopy
version. This environment can be easily started using the ESI JupyterHub
Syncopy makes heavy use of temporary files, which may become large (> 100 GB).
The storage location can be set using the environmental variable
by default points to your home directory:
The performance of Syncopy strongly depends on the read and write speed in this folder. On the ESI cluster, the variable is set to use the high performance storage: